## SSCf384. Topic 9. Computational Statistics

and

Mf394C.
Computational Statistics

and

CAMf394 Computational
Statistics

Summer 2009 RLM 11.176 MTWTHF 10:00 - 11:30 a.m. June 4, 2009 –
July 9, 2009

**Course Description**. A course in modern
computationally-intensive statistical methods including simulation,
optimization methods, Monte Carlo integration, maximum likelihood /
EM parameter estimation, Markov chain Monte Carlo methods, resampling
methods, non-parametric density estimation. Prerequisite: Graduate
Standing and Mathematics 362K and 378K, or consent of instructor.

We will use the statistics package R, which is a free program so I
expect that all students will download it to use. I will provide
explanations of how to use these programs and most of the computer
work in the course will be modifying code which is provided.

The grading in the course will be based on homework assignments
and two take-home exams. Students may collaborate on the homework
assignments, but the take-home exams must be done individually.

**Textbook**: Required: *Computational Statistics*
by Geof H. Givens and Jennifer A.Hoeting, Wiley, 2005.

Recommended:
Statistical Computing in R by Maria Rizzo, Chapman and Hall, 2007.

These books will be available on 2-hour reserve in the RLM
library.

If you read the Preface of the textbook, you will see that the
authors assume familiarity with several statistical techniques that
are beyond the level of the prerequisite for this course. We will not
cover chapters that use all of these, and for those we do cover, I
expect to teach those statistical topics as well as the computational
topics. In particular, students should already be familiar with
maximum likelihood estimation and regression. Other topics will be
introduced in the course as needed.

There is a suggestion in the Preface for the chapters/topics to be
covered in a one-semester course. This seems too ambitious to me for
this particular class, so I believe we will follow a "more
leisurely pace" as they say in the Preface. It will be a small
class and it will be a discussion / lecture class more than mainly a
lecture class.